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Data Sharing: Social and Normative - ISWC


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Given at ISWC 2009 as a part of "Legal and Social Frameworks for Sharing Data on the Web" tutorial with Leigh Dodds and Tom Heath from Talis and Jordan Hatcher from Open Data Commons. 25 Oct 2009. …

Given at ISWC 2009 as a part of "Legal and Social Frameworks for Sharing Data on the Web" tutorial with Leigh Dodds and Tom Heath from Talis and Jordan Hatcher from Open Data Commons. 25 Oct 2009. (

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  • 1. data sharing: social and normative kaitlin thaney program manager, science commons chantilly, va - ISWC - 25 oct 2009 This presentation is licensed under the CreativeCommons-Attribution-3.0 license.
  • 2. make sharing easy, legal and scalable integrated approach building part of the infrastructure for knowledge sharing
  • 3. I am not a lawyer. (first things first)
  • 4. social and normative issues human involvement, added roadblocks implications of FLOSS interoperability, design decisions how to navigate?
  • 5. the data web
  • 6. needs to be legally and technically accessible
  • 7. “ By open access to the literature, we mean its free availability on the public internet, permitting users to read, download, copy, distribute, print, search, or link to the full texts of the articles, crawl them for indexing, pass them as data to software, or use them for any other lawful purpose, without financial, legal or technical barriers other than those inseparable from gaining access to the internet itself.” Image from the Public Library of Science, licensed to the public, under CC-BY-3.0
  • 8. as a means to achieve Open Access but what about data?
  • 9. knowledge? journal articles data ontologies annotations plasmids and cell lines
  • 10. knowledge? journal articles data ontologies annotations plasmids and cell lines ... how to treat? like content? software?
  • 11. early days of WWW no licenses (even free) debate over code CERN’s decision view/edit source network effects
  • 12. the data web still in its infancy ...
  • 13. “the future is here ... just unevenly distributed” - william gibson (i.e., linked data, W3C, neurocommons...)
  • 14. (social) implications of FLOSS toggles
  • 15. free/libre license ethos notion of licensing to make more free
  • 16. © “creative expression”
  • 17. is it creative?
  • 18. is it creative?
  • 19. is it creative?
  • 20. category errors
  • 21. the problem of... Non-Commercial for data
  • 22. Non-Commercial what’s a commercial use of the data web?
  • 23. the problem of... Share Alike for data
  • 24. issue of license proliferation whatever you do to the least of the databases, you do to the integrated system (the most restrictive wins) risk for unintended consequences
  • 25. the problem of... Attribution for data
  • 26. social aspect of semantics
  • 27. agreement is hard.
  • 28. espresso coffee cafe kopi cafezinho latte koffee mocha americano
  • 29. “choice” or interoperability. (pick one)
  • 30. converge on common names “coffee” “cafe” coffee “kopi”
  • 31. national law hurdles sui generis, “sweat of the brow” Crown copyright “level of skill” how internat’l data sharing efforts are affected?
  • 32. protection instinct / culture of control quality control, integrity concerns “my data”, interpretation issues fear, uncertainty, doubt (FUD)
  • 33. <mosquitos><transmit><malaria> validation, provenance relationship mapping, citation? what rights? still not fully automated
  • 34. a norms approach
  • 35. a non-license means to request certain behavior community norms best practices, terms of use
  • 36. attribution vs. citation which one applies? which is best fit? what’s the difference? “credit where credit is due”
  • 37. attribution “the requirement to acknowledge or credit the author of a work which is used or appears in another work” citation “reference to a published or unpublished source” ... prime purpose is of “intellectual honesty” (via wikipedia)
  • 38. attribution: (legal entity) “triggered by making of a copy” does it apply to facts? how? (papers, ontologies, data) “in a manner specified by ...” attribution stacking
  • 39. how to perform? how much is enough? unintentional infringement (example, ontologies) does it apply?
  • 40. citation: (gentle(wo)man’s club) legal requirement? interoperability? credit where credit is due entrenched scientific norm
  • 41. we shouldn’t use the law to make it hard to do the wrong thing ...
  • 42. need for a legally accurate and simple solution reducing or eliminating the need to make the distinction of what’s protected requires modular, standards based approach to licensing
  • 43. calls for data providers to waive all rights necessary for data extraction and re-use requires provider place no additional obligations (like share-alike) to limit downstream use request behavior (like attribution) through norms and terms of use
  • 44. ... must promote legal predictability and certainty. ... must be easy to use and understand. ... must impose the lowest possible transaction costs on users. full text:
  • 45. set of principles (not license) open, accessible, interoperable know it’s safe to play
  • 46. impose “toggles” through norms, terms of use best fit for the discipline doesn’t limit downstream use
  • 47. at best, we’re partially right. at worst, we’re really wrong.
  • 48. resist the temptation to treat as property embrace the potential to treat instead as a network resource
  • 49. scalability is key “get law out of the way” build + allow for network effects
  • 50. the right to fix our mistakes.
  • 51. (remember Prodigy and AOL?)
  • 52. thank you.